An Energy-Efficient and Approximate Accelerator Design for Real-Time Canny Edge Detection

2020 ◽  
Vol 39 (12) ◽  
pp. 6098-6120
Author(s):  
Leonardo Bandeira Soares ◽  
Julio Oliveira ◽  
Eduardo Antonio César da Costa ◽  
Sergio Bampi
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Energy Efficient ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
Accelerator Design

scholarly journals SURVEY ON DISTRIBUTED CANNY EDGE DETECTOR WITH FPGA

2015 ◽  
Vol 3 (3) ◽  
pp. 51-61
Author(s):  
Poonam S. Deokar ◽  
Anagha P. Khedkar
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Large Scale ◽  
Attractive Alternative ◽  
Edge Detector ◽  
Canny Edge Detection ◽  
Canny Edge Detector ◽  
Canny Edge ◽  
Canny Algorithm ◽  
Real Time Applications

The Edge can be defined as discontinuities in image intensity from one pixel to another. Modem image processing applications demonstrate an increasing demand for computational power and memories space. Typically, edge detection algorithms are implemented using software. With advances in Very Large Scale Integration (VLSI) technology, their hardware implementation has become an attractive alternative, especially for real-time applications. The Canny algorithm computes the higher and lower thresholds for edge detection based on the entire image statistics, which prevents the processing of blocks independent of each other. Direct implementation of the canny algorithm has high latency and cannot be employed in real-time applications. To overcome these, an adaptive threshold selection algorithm may be used, which computes the high and low threshold for each block based on the type of block and the local distribution of pixel gradients in the block. Distributed Canny Edge Detection using FPGA reduces the latency significantly; also this allows the canny edge detector to be pipelined very easily. The canny edge detection technique is discussed in this paper.

scholarly journals Early warning flood detector adopting camera by Sobel Canny edge detection algorithm method

2021 ◽  
Vol 22 (3) ◽  
pp. 1796
Author(s):  
Satryo B. Utomo ◽  
Januar Fery Irawan ◽  
Rizqi Renafasih Alinra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Detection System ◽  
Water Levels ◽  
Level Gauge ◽  
Canny Edge Detection ◽  
Canny Edge

Early warning of floods is an essential part of disaster management. Various automatic detectors have been developed in flood mitigation, including cameras. But reliability and accuracy have not been improved. Besides, the use of monitoring devices has been employed to monitor water levels in various water building facilities. The early warning flood detector was carried out with a sensor camera using an orange ball that floats near the water level gauge in a bounding box. This approach uses the integration of computer vision and image processing, namely digital image processing techniques, with Sobel Canny edge detection (SCED) algorithms to detect quickly and accurately water levels in real-time. After the water level is measured, a flood detection process is carried out based on the specified water level. According to the results of experiments in the laboratory, it has been shown that the proposed approach can detect objects accurately and fast in real-time. Besides, from the water level detection experiment, good results were obtained. Therefore, the object detection system and water level can be used as an efficient and accurate early detection system for flood disasters.

scholarly journals Indian Sign Language Recognition Using Canny Edge Detection

2021 ◽  
Vol 10 (3) ◽  
pp. 1576-1583
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Sign Language ◽  
Hearing Impaired ◽  
Ordinary People ◽  
Sign Languages ◽  
Data Set ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
Indian Sign Language

n our society, it is very difficult for hearing impaired and speech impaired people to communicate with ordinary people. They use sign languages to communicate, which use visually transmitted sign patterns, generally includes hand gestures. Sign languages being difficult to learn and non-universal, there is a barrier of communication between the hearing impaired and ordinary people. To break this barrier a system is required that can convert sign language to voice and vice versa in real-time. Here, we propose a real-time two-way system, for communication between hearing-impaired and normal people, which converts the Indian Sign Language (ISL) letters into equivalent alphabet letters and vice versa. In the proposed system, using a camera, images of ISL hand gestures are captured. Then Image pre-processing is done so that these images are ready for feature extraction. Here, a novel approach of using the Canny Edge Detection Algorithm. Once the necessary details are extracted from the image, it is matched with the data set, which is classified using Convolutional Neural Network, and the corresponding text is generated. This text is converted into a voice. Similarly, using a microphone, the voice input of an ordinary person is captured and converted into text. This text is then matched with the data set and a corresponding sign is generated. This system reduces the gap in communication between hearing-impaired and ordinary people. Our method provides 98 % accuracy for the 35 alphanumeric gestures of ISL

scholarly journals Real Time Identification of Railway Track Surface Faults using Canny Edge Detector and 2D Discrete Wavelet Transform

2020 ◽  
Vol 4 (2) ◽  
pp. 53-60 ◽  
Author(s):  
Ali Akbar Shah ◽  
Bhawani S. Chowdhry ◽  
Tayab D. Memon ◽  
Imtiaz H. Kalwar ◽  
J. Andrew Ware
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Wavelet Transformation ◽  
Surface Damage ◽  
Railway Track ◽  
Discrete Wavelet ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
Real Time Identification ◽  
Track Surface

Usually, railway accidents are caused by train derailment, the mechanical failure of tracks, such as broken rails often caused by lack of railway condition monitoring. Such monitoring could identify track surface faults, such as squats, that act as a catalyst for the track to crack and ultimately break. The research presented in this paper enables real-time identification of railway track faults using image processing techniques such as Canny edge detection and 2D discrete wavelet transformation. The Canny edge detection outperforms traditional track damage detection techniques including Axle Based Acceleration using Inertial Measurement Units and is as reliable as Fiber Bragg Grating. The Canny edge detection employed can identify squats in real-time owing to its specific threshold amplitude using a camera module mounted on a specially designed handheld Track Recording Vehicle (TRV). The 2D discrete wavelet transformation validates the insinuation of the Canny edge detector regarding track damage and furthermore determines damage severity, by applying high sub band frequency filter. The entire algorithm works on a Raspberry Pi 3 B+ utilizing an OpenCV API. When tested using an actual rail track, the algorithm proved reliable at determining track surface damage in real-time. Although wavelet transformation performs better than Canny edge detection in terms of determining the severity of track surface damage, it has processing overheads that become a bottleneck in real-time. To overcome this deficiency a very effective two-stage process has been developed.

scholarly journals A performance analysis for real-time flood monitoring using image-based processing

2020 ◽  
Vol 17 (2) ◽  
pp. 793
Author(s):  
Qianyu Zhang ◽  
Nattha Jindapetch ◽  
Rakkrit Duangsoithong ◽  
Dujdow Buranapanichkit
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Working Environment ◽  
Outdoor Environment ◽  
Image Processing Technique ◽  
Real Time System ◽  
Canny Edge Detection ◽  
The Real ◽  
Flood Monitoring ◽  
Canny Edge

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Nowadays, various image-based methods have been used in the area of monitoring. Whereas the precision of detection objects and real-time processing are the key issues for many applications. Considering the limitation of the working environment, the higher correctness and faster operating time can guarantee the work efficiency. In this paper, the image-based methods have been studied to monitoring the state of the flood in the real-time system. The performance of each image processing technique has been evaluated based on accuracy and processing time. In the flood monitoring system, the variation of important parameters can cause the change of performance and the effect of the variable parameters has been demonstrated from the experiment results. After comparing to the other image-based techniques, canny edge detection presents the best one, which also has better repeatability with the source image from different locations. Consequently, the improved canny edge detection method has been proved that can work very well on the real hardware in the outdoor environment.</span>

Real-time canny edge detection parallel implementation for FPGAs

2010 ◽  
Author(s):  
Christos Gentsos ◽  
Calliope-Louisa Sotiropoulou ◽  
Spiridon Nikolaidis ◽  
Nikolaos Vassiliadis
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Parallel Implementation ◽  
Canny Edge Detection ◽  
Canny Edge
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